MARC details
| 000 -LEADER |
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| fixed length control field |
04437cam a22005057i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
18833952 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20210615161209.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
151027s2013 nyua 001 0 eng d |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
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| LC control number |
2015473155 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
143025761X |
| Qualifying information |
(pbk.) |
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| International Standard Book Number |
9781430257615 |
| Qualifying information |
(pbk.) |
|
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| Canceled/invalid ISBN |
9781430257622 |
| Qualifying information |
(electronic bk.) |
| 035 ## - SYSTEM CONTROL NUMBER |
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| System control number |
(OCoLC)ocn854299809 |
| 037 ## - SOURCE OF ACQUISITION |
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| Source of stock number/acquisition |
Textstream, 1120 Rte 22 E, Bridgewater, NJ, USA, 08807, (908)5417442 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
CDX |
| Language of cataloging |
eng |
| Transcribing agency |
ATU |
| Description conventions |
rda |
| Modifying agency |
OCLCQ |
| -- |
SISMU |
| -- |
YDXCP |
| -- |
OCLCQ |
| -- |
NYP |
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BTCTA |
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DEBSZ |
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TOH |
| -- |
OCLCQ |
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CDN |
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OCLCQ |
| -- |
OCLCF |
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OCLCQ |
| -- |
DLC |
| 042 ## - AUTHENTICATION CODE |
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| Authentication code |
lccopycat |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA76.9.B45 |
| Item number |
Z2 2013 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
005.74 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zadrozny, Peter, |
| Dates associated with a name |
1943- |
| Relator term |
author. |
| 9 (RLIN) |
18032 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Big data analytics using Splunk / |
| Statement of responsibility, etc. |
Peter Zadrozny, Raghu Kodali. |
| 246 1# - VARYING FORM OF TITLE |
|---|
| Display text |
Subtitle on cover: |
| Title proper/short title |
Deriving operational intelligence from social media, machine data, existing data warehouses, and other real-time streaming sources |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
[New York, N.Y.] : |
| Name of producer, publisher, distributor, manufacturer |
Apress, |
| Date of production, publication, distribution, manufacture, or copyright notice |
[2013] |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xix, 353 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
24 cm |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
|---|
| General note |
"The expert's voice in big data."--Cover. |
|
|---|
| General note |
Includes index. |
| 505 00 - FORMATTED CONTENTS NOTE |
|---|
| Title |
Big Data and Splunk -- |
| -- |
Getting Data into Splunk -- |
| -- |
Processing and Analyzing the Data -- |
| -- |
Visualizing the Results -- |
| -- |
Defining Alerts -- |
| -- |
Web Site Monitoring -- |
| -- |
Using Log Files To Create Advanced Analytics -- |
| -- |
The Airline On-Time Performance Project -- |
| -- |
Getting the Flight Data into Splunk -- |
| -- |
Analyzing Airlines, Airports, Flights, and Delays -- |
| -- |
Analyzing a Specific Flight Over the Years -- |
| -- |
Analyzing Tweets -- |
| -- |
Analyzing Foursquare Check-Ins -- |
| -- |
Sentiment Analysis -- |
| -- |
Remote Data Collection -- |
| -- |
Scaling and High Availability -- |
| -- |
The Performance of Splunk -- |
| -- |
Useful Splunk Apps. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Big Data Analytics Using Splunk is a hands-on book showing how to process and derive business value from big data in real time. Examples in the book draw from social media sources such as Twitter (tweets) and Foursquare (check-ins). You also learn to draw from machine data, enabling you to analyze, say, web server log files and patterns of user access in real time, as the access is occurring. Gone are the days when you need be caught out by shifting public opinion or sudden changes in customer behavior. Splunks easy to use engine helps you recognize and react in real time, as events are occurring. Splunk is a powerful, yet simple analytical tool fast gaining traction in the fields of big data and operational intelligence. Using Splunk, you can monitor data in real time, or mine your data after the fact. Splunks stunning visualizations aid in locating the needle of value in a haystack of a data. Geolocation support spreads your data across a map, allowing you to drill down to geographic areas of interest. Alerts can run in the background and trigger to warn you of shifts or events as they are taking place. With Splunk you can immediately recognize and react to changing trends and shifting public opinion as expressed through social media, and to new patterns of eCommerce and customer behavior. The ability to immediately recognize and react to changing trends provides a tremendous advantage in todays fast-paced world of Internet business. Big Data Analytics Using Splunk opens the door to an exciting world of real-time operational intelligence. Built around hands-on projects Shows how to mine social media Opens the door to real-time operational intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big data. |
| 9 (RLIN) |
18033 |
|
|---|
| Topical term or geographic name entry element |
Data mining. |
| 9 (RLIN) |
2253 |
|
|---|
| Topical term or geographic name entry element |
Automatic data collection systems. |
| 9 (RLIN) |
11253 |
|
|---|
| Topical term or geographic name entry element |
Automatic data collection systems. |
| Source of heading or term |
fast |
| Authority record control number or standard number |
(OCoLC)fst00822733 |
| 9 (RLIN) |
11253 |
|
|---|
| Topical term or geographic name entry element |
Big data. |
| Source of heading or term |
fast |
| Authority record control number or standard number |
(OCoLC)fst01892965 |
| 9 (RLIN) |
18033 |
|
|---|
| Topical term or geographic name entry element |
Data mining. |
| Source of heading or term |
fast |
| Authority record control number or standard number |
(OCoLC)fst00887946 |
| 9 (RLIN) |
2253 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kodali, Raghu R., |
| Relator term |
author. |
| 9 (RLIN) |
18034 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Contributor biographical information |
| Uniform Resource Identifier |
<a href="https://www.loc.gov/catdir/enhancements/fy1610/2015473155-b.html">https://www.loc.gov/catdir/enhancements/fy1610/2015473155-b.html</a> |
|
|---|
| Materials specified |
Publisher description |
| Uniform Resource Identifier |
<a href="https://www.loc.gov/catdir/enhancements/fy1610/2015473155-d.html">https://www.loc.gov/catdir/enhancements/fy1610/2015473155-d.html</a> |
|
|---|
| Materials specified |
Table of contents only |
| Uniform Resource Identifier |
<a href="https://www.loc.gov/catdir/enhancements/fy1610/2015473155-t.html">https://www.loc.gov/catdir/enhancements/fy1610/2015473155-t.html</a> |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
copycat |
| d |
2 |
| e |
ncip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
ATU Book |
